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20172022
most citedDefending Person Detection Against Adversarial Patch Attack by using Universal Defensive Frame

22 citations · 110 across the 22 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

cs.CV2020

Comprehensive Facial Expression Synthesis using Human-Interpretable Language

Joanna Hong, Jung Uk Kim, Sangmin Lee +1

Recent advances in facial expression synthesis have shown promising results using diverse expression representations including facial action units. Facial action units for an elabo…

cs.CV2020★ 16 cited

Investigating Vulnerability to Adversarial Examples on Multimodal Data Fusion in Deep Learning

Youngjoon Yu, Hong Joo Lee, Byeong Cheon Kim +2

The success of multimodal data fusion in deep learning appears to be attributed to the use of complementary in-formation between multiple input data. Compared to their predictive p…

cs.CV2020★ 4 cited

Efficient Ensemble Model Generation for Uncertainty Estimation with Bayesian Approximation in Segmentation

Hong Joo Lee, Seong Tae Kim, Hakmin Lee +2

Recent studies have shown that ensemble approaches could not only improve accuracy and but also estimate model uncertainty in deep learning. However, it requires a large number of…

cs.CV2020

Revisiting Role of Autoencoders in Adversarial Settings

Byeong Cheon Kim, Jung Uk Kim, Hakmin Lee +1

To combat against adversarial attacks, autoencoder structure is widely used to perform denoising which is regarded as gradient masking. In this paper, we revisit the role of autoen…

cs.CV2020★ 1 cited

Robust Ensemble Model Training via Random Layer Sampling Against Adversarial Attack

Hakmin Lee, Hong Joo Lee, Seong Tae Kim +1

Deep neural networks have achieved substantial achievements in several computer vision areas, but have vulnerabilities that are often fooled by adversarial examples that are not re…